Developing a understanding of the Beer landscape is a critical step as BeerMeUp grows into an organization that has the national attention of beer Connoisseurs across the World. This report outlines the strategic approach to the market that will support the execution of future Beer Products across the Beer Portfolio. Additionally, the sustainment of existing operations is substantial to the ongoing success that has made BeerMeUp successful for the last 14 years. This report is to provide a solid under of the US Beer market so BeerMeUp can gain a competitive advantage over the vast number of Beer Producers.
As we discussed in the executive summary, it is vitally important to understand the beer landscape. Reviewing the Map below, the opportunity is tremendous in many large states to open a Brewery, such as California and Texas due to the population size; however, Florida might be a state with not as many breweries with a dense population. As we explore the data in this report, we will identify other areas of interest.
In contrast to the breweries per state in the map above, the Beers by State is another good way to review the data. While Florida doesn’t have many local breweries as mentioned above, it has a lot of beers in the state and it might be a good location for the next brewery because Florida is a state that does drink a lot of different types of beer. However, additional testing will be needed, but a good target for a location.
As you continue to do the exploratory research, we implemented an interactive matrix will outline the number of Beers produced by each state. There are very good targets to do further investigation for your next location. This matrix will help guide you to next hot market as you begin to understand what beers and breweries work in which geography across the US.
| x | |
|---|---|
| CO | 47 |
| CA | 39 |
| MI | 32 |
| OR | 29 |
| TX | 28 |
| PA | 25 |
| MA | 23 |
| WA | 23 |
| IN | 22 |
| WI | 20 |
| NC | 19 |
| IL | 18 |
| NY | 16 |
| VA | 16 |
| FL | 15 |
| OH | 15 |
| MN | 12 |
| AZ | 11 |
| VT | 10 |
| ME | 9 |
| MO | 9 |
| MT | 9 |
| CT | 8 |
| AK | 7 |
| GA | 7 |
| MD | 7 |
| OK | 6 |
| IA | 5 |
| ID | 5 |
| LA | 5 |
| NE | 5 |
| RI | 5 |
| HI | 4 |
| KY | 4 |
| NM | 4 |
| SC | 4 |
| UT | 4 |
| WY | 4 |
| AL | 3 |
| KS | 3 |
| NH | 3 |
| NJ | 3 |
| TN | 3 |
| AR | 2 |
| DE | 2 |
| MS | 2 |
| NV | 2 |
| DC | 1 |
| ND | 1 |
| SD | 1 |
| WV | 1 |
As we continue down understand the market in totality, our research drove us to understand the next variety of Beers. While we are only showing the Top and Bottom 6 beers based on the Beer Identification in order, the rest of the data is summarized in the report. This list is not meant to be exhaustive, it is meant to show you the magnitude of beers that are being sold and distributed across the US.
| Brew_ID | BreweryName | Beer_ID | ABV | IBU | Beer_Style | Beer_Ounces | Brewery_Name | City | State |
|---|---|---|---|---|---|---|---|---|---|
| 1 | Get Together | 2692 | 0.045 | 50 | American IPA | 16 | NorthGate Brewing | Minneapolis | MN |
| 1 | Maggie’s Leap | 2691 | 0.049 | 26 | Milk / Sweet Stout | 16 | NorthGate Brewing | Minneapolis | MN |
| 1 | Wall’s End | 2690 | 0.048 | 19 | English Brown Ale | 16 | NorthGate Brewing | Minneapolis | MN |
| 1 | Pumpion | 2689 | 0.060 | 38 | Pumpkin Ale | 16 | NorthGate Brewing | Minneapolis | MN |
| 1 | Stronghold | 2688 | 0.060 | 25 | American Porter | 16 | NorthGate Brewing | Minneapolis | MN |
| 1 | Parapet ESB | 2687 | 0.056 | 47 | Extra Special / Strong Bitter (ESB) | 16 | NorthGate Brewing | Minneapolis | MN |
| Brew_ID | BreweryName | Beer_ID | ABV | IBU | Beer_Style | Beer_Ounces | Brewery_Name | City | State | |
|---|---|---|---|---|---|---|---|---|---|---|
| 2405 | 556 | Pilsner Ukiah | 98 | 0.055 | NA | German Pilsener | 12 | Ukiah Brewing Company | Ukiah | CA |
| 2406 | 557 | Heinnieweisse Weissebier | 52 | 0.049 | NA | Hefeweizen | 12 | Butternuts Beer and Ale | Garrattsville | NY |
| 2407 | 557 | Snapperhead IPA | 51 | 0.068 | NA | American IPA | 12 | Butternuts Beer and Ale | Garrattsville | NY |
| 2408 | 557 | Moo Thunder Stout | 50 | 0.049 | NA | Milk / Sweet Stout | 12 | Butternuts Beer and Ale | Garrattsville | NY |
| 2409 | 557 | Porkslap Pale Ale | 49 | 0.043 | NA | American Pale Ale (APA) | 12 | Butternuts Beer and Ale | Garrattsville | NY |
| 2410 | 558 | Urban Wilderness Pale Ale | 30 | 0.049 | NA | English Pale Ale | 12 | Sleeping Lady Brewing Company | Anchorage | AK |
As a item to pay attention as you begin to look through the analysis, it is essential to not just look at the raw numbers, but rather understand and realize that there are fields in the data set that have invalid or N/A columns. As you work with your data science teams, they will be critical as you being the basic regression testing because these type of data irregularities can cause data integrity issues within results. The table below is meant to be a quick summary of the columns that have invalid or N/A Columns
| x | |
|---|---|
| Brew_ID | 0 |
| BreweryName | 0 |
| Beer_ID | 0 |
| ABV | 62 |
| IBU | 1005 |
| Beer_Style | 0 |
| Beer_Ounces | 0 |
| Brewery_Name | 0 |
| City | 0 |
| State | 0 |
As we begin analyzing the data in the brewery’s and types of beer, two important factors need to be understood and analyzed. Median Alcohol by Volume (ABV) and International Bitterness Units (IBU) are essential in understanding what factors are important in each states. For example, the beer drinkers in Alaska like bitter beer (IBU = 46) as compared to Arizona (IBU = 20.5). While reviewing this is a matrix is difficult, the data science team can use this data and decorate with other variables are you begin developing and marketing your new beer and or brewery.
| State | ABV | IBU |
|---|---|---|
| AK | 0.0560 | 46.0 |
| AL | 0.0600 | 43.0 |
| AR | 0.0520 | 39.0 |
| AZ | 0.0550 | 20.5 |
| CA | 0.0580 | 42.0 |
| CO | 0.0605 | 40.0 |
| CT | 0.0600 | 29.0 |
| DC | 0.0625 | 47.5 |
| DE | 0.0550 | 52.0 |
| FL | 0.0570 | 55.0 |
| GA | 0.0550 | 55.0 |
| HI | 0.0540 | 22.5 |
| IA | 0.0555 | 26.0 |
| ID | 0.0565 | 39.0 |
| IL | 0.0580 | 30.0 |
| IN | 0.0580 | 33.0 |
| KS | 0.0500 | 20.0 |
| KY | 0.0625 | 31.5 |
| LA | 0.0520 | 31.5 |
| MA | 0.0540 | 35.0 |
| MD | 0.0580 | 29.0 |
| ME | 0.0510 | 61.0 |
| MI | 0.0620 | 35.0 |
| MN | 0.0560 | 44.5 |
| MO | 0.0520 | 24.0 |
| MS | 0.0580 | 45.0 |
| MT | 0.0550 | 40.0 |
| NC | 0.0570 | 33.5 |
| ND | 0.0500 | 32.0 |
| NE | 0.0560 | 35.0 |
| NH | 0.0550 | 48.5 |
| NJ | 0.0460 | 34.5 |
| NM | 0.0620 | 51.0 |
| NV | 0.0600 | 41.0 |
| NY | 0.0550 | 47.0 |
| OH | 0.0580 | 40.0 |
| OK | 0.0600 | 35.0 |
| OR | 0.0560 | 40.0 |
| PA | 0.0570 | 30.0 |
| RI | 0.0550 | 24.0 |
| SC | 0.0550 | 30.0 |
| SD | 0.0600 | NA |
| TN | 0.0570 | 37.0 |
| TX | 0.0550 | 33.0 |
| UT | 0.0400 | 34.0 |
| VA | 0.0565 | 42.0 |
| VT | 0.0550 | 30.0 |
| WA | 0.0555 | 38.0 |
| WI | 0.0520 | 19.0 |
| WV | 0.0620 | 57.5 |
| WY | 0.0500 | 21.0 |
While it is important to understand the raw data, this bar chart will allow you to quickly decipher which states prefer which Beer IBU.
Just as important as the IBU scale, the following ABV bar chart will allow you to quickly decipher which states prefer which Beer ABV
Alcohol by Volume Chart
Another good example of how you can utilize the data set to your competitive advantage is understanding which State has the Maximum ABV and which states has the most bitter Beer. The following table outlines the top state that has the IBU and ABV.
| Brew_ID | BreweryName | Beer_ID | ABV | IBU | Beer_Style | Beer_Ounces | Brewery_Name | City | State | |
|---|---|---|---|---|---|---|---|---|---|---|
| 375 | 52 | Lee Hill Series Vol. 5 - Belgian Style Quadrupel Ale | 2565 | 0.128 | NA | Quadrupel (Quad) | 19.2 | Upslope Brewing Company | Boulder | CO |
| Brew_ID | BreweryName | Beer_ID | ABV | IBU | Beer_Style | Beer_Ounces | Brewery_Name | City | State | |
|---|---|---|---|---|---|---|---|---|---|---|
| 1857 | 375 | Bitter Bitch Imperial IPA | 980 | 0.082 | 138 | American Double / Imperial IPA | 12 | Astoria Brewing Company | Astoria | OR |
As we look into the statistics of the Alcohol by Volume in Table H, the data shows that the Mean ABV is almost 6% but is as high as 10% and as low at 0.1%.
| vars | n | mean | sd | median | trimmed | mad | min | max | range | skew | kurtosis | se | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| X1 | 1 | 2348 | 0.0597734 | 0.0135417 | 0.056 | 0.0583888 | 0.0118608 | 0.001 | 0.128 | 0.127 | 0.9572529 | 1.13642 | 0.0002795 |
Based on the data set, there is a positive correlation and a linear relationship between IBU and ABV, as seen in Table I. As the ABV increases, so does the IBU. This is essential in your creation of a brewery and new beers to understand that this is a standard relationship in these two variables.
In our box and whisker plot in Table K, this is another way to analyze the beers per state. The competitive intelligence that can be gained is the typical sweet spot, median and mean, for where the majority of the beers are being produced by that state based on IBU and ABV. Depending on the appetite, staying in this range is a strategic decision in how your build breweries or formulate the beer.
In conclusion, it is essential to understand the market as the company grows. While there are many breweries and beers across the United States, it is essential in understanding the beerscape of which market you enter. As discussed in many of the charts and graphs above, different areas of the country are accustomed to higher and lower alcohol content and more or less bitter brews. This could be attributed to ingredient availability, but it something that will help the company understand the market because it is the local rules that will prevail.
As the company begins to sift through all the data, there are multiple approaches to take. For example, the Colorado region since has the largest amount of breweries and most diverse brewing styles across the nation. However, that maker may be saturated and the barriers of entry may be difficult. Another strategy would be to utilize the BeerMeUp’s already strong product line, utilize the knowledge and strength of the organization, and target States that have only a few breweries and local beers to establish the market. States like Florida, Alabama, and Kansas could be prime targets as both states have large university settings.
Overall, with all the of the information contained in the report, we believe that BeerMeUp is in a good competitive situation because of the forward thinking approach using data science techniques to gain even more market share.
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